Multi-attribute information technology project selection using fuzzy axiomatic design

Purpose - Significant productivity improvements have been experienced in business by information technology (IT) implementations in latest decades. However, IT project selection is an important problem because a significant part of IT expenditure is wasted and almost half of IT projects realize no n...

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Bibliographic Details
Published in:Journal of enterprise information management 2005-06, Vol.18 (3), p.275-288
Main Authors: Kulak, Osman, Kahraman, Cengiz, Öztay i, Ba ar, Tanya, Mehmet
Format: Article
Language:English
Subjects:
Decision making models
Design
Expenditures
Fuzzy logic
Fuzzy sets
Information technology
Manufacturing
Multiple criteria decision making
Product development
Productivity
Project evaluation
Set theory
Software
Systems design
User services
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Summary:Purpose - Significant productivity improvements have been experienced in business by information technology (IT) implementations in latest decades. However, IT project selection is an important problem because a significant part of IT expenditure is wasted and almost half of IT projects realize no net benefits. Since axiomatic design (AD) has the characteristics of multi-attribute evaluation, it is proposed for multi-attribute comparison of information technology systems (ITS).Design methodology approach - The comparison of ITS is made for the cases of both complete and incomplete information. The crisp AD approach for complete information and the fuzzy AD approach for incomplete information are developed. The numerical applications of both crisp and fuzzy AD approaches in the comparison of ITS are also given.Findings - The AD approach takes into account the design range of each criterion, determined by the designer. Thus, the alternative providing the design ranges is selected in AD approach while the alternative meeting the criteria at their best levels is selected in many other methods. This opportunity is not possible when many other existing methods such as AHP, fuzzy AHP, and scoring models are used. The AD approach also differs from many other existing methods from the point of the rejection of an alternative when it does not meet the design range of any criterion.Research limitations implications - For future research, it is suggested that researchers study weighted crisp and fuzzy AD approaches.Originality value - This paper is the first which develops the fuzzy AD approach and uses it in the comparison of ITS.
ISSN:1741-0398
1758-7409
DOI:10.1108/17410390510591978